Although preferences have traditionally been studied in fields such as economic
decision making, social choice theory, and Operations Research, they have nowadays
found significant interest in computational fields such as Artificial Intelligence,
Databases, and Human-computer interaction. This broadened scope of preferences
leads to new types of preference models, new problems for applying preference
structures, and new kinds of benefits. Explicit preference modeling provides a
declarative way to choose among alternatives, whether these are solutions of
problems to solve, answers of database queries, decisions of a computational agent,
plans of a robot, and so on. Preference-based systems allow finer-grained control
over computation and new ways of interactivity, and therefore provide more
satisfactory results and outcomes. Preference models may also provide a clean
understanding, analysis, and validation of heuristic knowledge used in existing
systems such as heuristic orderings, dominance rules, and heuristic rules.
Preferences are studied in many areas of Artificial Intelligence such as knowledge
representation, multi-agent systems, constraint satisfaction, decision making,
decision-theoretic planning, and beyond. Preferences are inherently a
multi-disciplinary topic, of interest to AI, Databases, Logic Programming,
Operation Research, and more.
The workshop promotes this broadened scope of preference handling and continues
a series of multidisciplinary workshops on preference handling (an
and a Dagstuhl-Seminar in 2004)
which have been very successful.
The workshop provides a forum for presenting advances in preference handling and for
exchanging experiences between researchers facing similar questions, but coming from
different fields. The workshop builds on the large number of AI researchers working on
preference-related issues and on an increasing number of database researchers, but
also seeks to attract researchers from multi-criteria decision making, economics,
etc. These different research areas are represented in the program committee.